docstr: Builds the basic inference graph for discriminator
docstr_tok: ["Builds","the","basic","inference","graph","for","discriminator"]
code: def _build_network_graph(self):
      """
      Builds the basic inference graph for discriminator
      """
      with tf.variable_scope("Discriminator", reuse=tf.AUTO_REUSE):
          w_init = tf.contrib.layers.xavier_initializer()
          noisy_input = tf.nn.dropout(
              self.input_data, self.do_ph, name="DO1"
          )
          fc1 = tf.layers.dense(
              noisy_input,
              self.hid_dim,
              kernel_initializer=w_init,
              activation=tf.nn.leaky_relu,
              name="Dense1",
          )
          fc2 = tf.layers.dense(
              fc1,
              self.hid_dim,
              kernel_initializer=w_init,
              activation=tf.nn.leaky_relu,
              name="Dense2",
          )
          self.prediction = tf.layers.dense(
              fc2, 1, kernel_initializer=w_init, name="Dense_Sig"
          )
  
imports: from __future__ import print_function, division
  import io
  import os
  import time
  import numpy
  import scipy
  import tensorflow
label_desc: Use image node_id 2 for calling the Discriminator obj's underlying member method code with example usage: obj._build_network_graph() without return types